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At least 1,567 records · Page 87

Functional Data Analysis in Wearable Body Sensor Networks

Improving response time of indirect room-size calorimeters is still an outstanding problem in metabolic research. Accurate estimates of instantaneous rates of gaseous exchange require numerical differentiation of measured gaseousgas concentrations. We propose a new method to estimate the instantaneous gaseousgas exchange rates in indirect calorimetry. In contrast to the previously developed techniques, the method addresses the problem of differentiation of gaseous concentrations as an ill-posed problem. By applying the method of regularization, the problem of differentiation is converted into a well-posed problem resulting in smooth and consistent gaseous exchange rates. The validity of the method is tested on a large dataset of calorimeter experiments which included 313 human experiments along with 231 alcohol combustion experiments. It is demonstrated that the method is able to reliably differentiate between the “unphysiological” process of alcohol combustion and physiological variations produced by human metabolism. The method also allowed unraveling the previously unreported relative kinetics of O2 consumption and Respiratory Quotient (RQ) in humans. It was found that the kinetics of oxidative fuel selection lags behind the energy expenditure in humans exhibiting some sort of oxidative inertia. The time lag varies from 2-3 min up to 30 min, depending on particular individual. No such lag was found in alcohol combustion experiments. In addition to the relative kinetics of substrate oxidation, two statistical indexes reflecting variability of minute-by-minute RQ were estimated. The indexes were the RQ’s standard deviation and RQ’s first-order derivative. Both indexes showed statistically significant difference between human experiments and alcohol combustion experiments. We conclude that the proposed method can consistently extract physiologically-relevant information from noisy calorimetry data and the aforesaid information can provide additional insights into the mechanism of metabolic fuel selection in humans.

54 ENVIRONMENTAL SCIENCES↗

Functional Data Analysis in Wearable Body Sensor Networks

Improving response time of indirect room-size calorimeters is still an outstanding problem in metabolic research. Accurate estimates of instantaneous rates of gaseous exchange require numerical differentiation of measured gaseousgas concentrations. We propose a new method to estimate the instantaneous gaseousgas exchange rates in indirect calorimetry. In contrast to the previously developed techniques, the method addresses the problem of differentiation of gaseous concentrations as an ill-posed problem. By applying the method of regularization, the problem of differentiation is converted into a well-posed problem resulting in smooth and consistent gaseous exchange rates. The validity of the method is tested on a large dataset of calorimeter experiments which included 313 human experiments along with 231 alcohol combustion experiments. It is demonstrated that the method is able to reliably differentiate between the “unphysiological” process of alcohol combustion and physiological variations produced by human metabolism. The method also allowed unraveling the previously unreported relative kinetics of O2 consumption and Respiratory Quotient (RQ) in humans. It was found that the kinetics of oxidative fuel selection lags behind the energy expenditure in humans exhibiting some sort of oxidative inertia. The time lag varies from 2-3 min up to 30 min, depending on particular individual. No such lag was found in alcohol combustion experiments. In addition to the relative kinetics of substrate oxidation, two statistical indexes reflecting variability of minute-by-minute RQ were estimated. The indexes were the RQ’s standard deviation and RQ’s first-order derivative. Both indexes showed statistically significant difference between human experiments and alcohol combustion experiments. We conclude that the proposed method can consistently extract physiologically-relevant information from noisy calorimetry data and the aforesaid information can provide additional insights into the mechanism of metabolic fuel selection in humans.

60 - APPLIED LIFE SCIENCES↗

deadtrees.earth — An open-access and interactive database for centimeter-scale aerial imagery to uncover global tree mortality dynamics

Excessive tree mortality is a global concern and remains poorly understood as it is a complex phenomenon. We lack global and temporally continuous coverage on tree mortality data. Ground-based observations on tree mortality, e.g., derived from national inventories, are very sparse, and may not be standardized or spatially explicit. Earth observation data, combined with supervised machine learning, offer a promising approach to map overstory tree mortality in a consistent manner over space and time. However, global-scale machine learning requires broad training data covering a wide range of environmental settings and forest types. Low altitude observation platforms (e.g., drones or airplanes) provide a cost-effective source of training data by capturing high-resolution orthophotos of overstory tree mortality events at centimeter-scale resolution. Here, we introduce deadtrees.earth, an open-access platform hosting more than two thousand centimeter-resolution orthophotos, covering more than 1,000,000 ha, of which more than 58,000 ha are manually annotated with live/dead tree classifications. This community-sourced and rigorously curated dataset can serve as a comprehensive reference dataset to uncover tree mortality patterns from local to global scales using space-based Earth observation data and machine learning models. This will provide the basis to attribute tree mortality patterns to environmental changes or project tree mortality dynamics to the future. The open nature of deadtrees.earth, together with its curation of high-quality, spatially representative, and ecologically diverse data will continuously increase our capacity to uncover and understand tree mortality dynamics.

Citizen science↗

Data and scripts associated with a manuscript investigating dissolved organic matter and microbial community linkages across seven globally distributed rivers

This data package is associated with the publication “Meta-metabolome ecology reveals that geochemistry and microbial functional potential are linked to organic matter development across seven rivers” submitted to Science of the Total Environment. This data package includes the data necessary to replicate the analyses presented within the manuscript to investigate dissolved organic matter (DOM) development across broad spatial distances and within divergent biomes. Specifically, we included the Fourier transform ion cyclotron mass spectrometry (FTICR-MS) data, geochemistry data, annotated metagenomic data, and results from ecological null modeling analyses in this data package. Additionally, we included the scripts necessary to generate the figures from the manuscript. Complete metagenomic data associated with this data package can be found at the National Center for Biotechnology (NCBI) under Bioproject PRJNA946291. This dataset consists of (1) four folders; (2) a file-level metadata (flmd) file; (3) a data dictionary (dd) file; (4) a factor sheet describing samples; and (5) a readme. The FTICR Data folder contains (1) the processed Fourier transform ion cyclotron mass spectrometry (FTICR-MS) data; (2) a transformation-weighted characteristics dendrogram generated from the FTICR-MS data; and (3) the script used to generate all FTICR-MS related figures. The Geochemical Data folder contains (1) the single geochemistry data file and (2) the R script responsible for generating associated figures. The Metagenomic Data folder contains (1) annotation information across different levels; (2) carbohydrate active enzyme (CAZyme) information from the dbCAN database (Yin et al., 2012); (3) phylogenetic tree data (FASTAs, alignments, and tree file); and (4) the scripts necessary to analyze all of these data and generate figures. The Null Modeling Data folder contains (1) data generated during null modeling for each river and all rivers combined and (2) the R scripts necessary to process the data. All files are .csv, .pdf, .tsv, .tre, .faa, .afa, .tree, or .R.

54 ENVIRONMENTAL SCIENCES↗

Federated Machine Learning-Based Anomaly Detection System for Synchrophasor Network Using Heterogeneous Data Sets: Preprint

Synchrophasor technology is widely deployed in the energy management system to monitor the grid health at micro level and perform necessary corrective actions in real time; however, integrated phasor devices and data aggregators are exposed to several cybersecurity threats. This paper proposes a federated ML(FML)-based ADS to detect several data integrity attacks in the synchrophasor network. The proposed approach integrates the horizontal FML technique and consists of substation-based local models and a control center-based global model. The proposed methodology includes training local models using heterogeneous data sets that include network and grid information and updating the global model through multiple iterations by sharing model gradients. Finally, the trained global model is applied to identify cyberattacks, normal operation, and physical events. To validate the proof of concept, we used synthetic data sets generated by Mississippi State University and Oak Ridge National Laboratory for training and testing the classification models using the National Renewable Energy Laboratory's high performance computing resources. Our experimental results, computed through several performance measures, reveal that the proposed approach shows consistent performance during the binary, three-class, and multiclass classifications while ensuring privacy of synchrophasor data.

anomaly detection system↗

Towards self-consistent integrated modeling of the tokamak pedestal, scrape-off layer, and divertor using SOLPS-ITER and EPED

A predictive, self-consistent integrated model of the tokamak edge plasma and neutral system has been developed and validated against experimental data from DIII-D, spanning from the divertor target and scrape-off layer to the top of the pedestal. The model uses the SOLPS-ITER fluid boundary plasma and neutral code to constrain the EPED prediction of the pedestal height and width by taking the separatrix temperature and density calculated from SOLPS as inputs to EPED. An empirical proxy function based on data from a subset of these discharges is then used to infer the ratio of density at the pedestal top to that at the separatrix based on the electron temperature at the divertor target. This allows the density at the top of the pedestal to be provided to EPED as well, so that knowledge of this quantity is no longer required a priori, while SOLPS radial transport coefficients are needed instead. The gas puff rate provided to SOLPS is then a primary model input for this forward model coupling (along with radial transport coefficients, which are kept fixed through each scan in this study). Comparisons with measurements from DIII-D density scans through a range of target conditions find significant pedestal pressure degradation as the density is increased towards detachment in three different divertor configurations, consistent with the experimental data in these ballooning-limited pedestal regimes.

core-edge integration↗

Task 12 Sustainability - Methodological Guidelines on Net Energy Analysis of Photovoltaic Electricity (2nd Edition)

Net Energy Analysis (NEA) is a structured, comprehensive method of quantifying the extent to which a given energy source is able to provide a net energy gain (i.e., an energy surplus) to the end user, after accounting for all the energy losses occurring along the chain of processes that are required to exploit it (i.e., for its extraction, processing and transformation into a usable energy carrier, and delivery to the end user), as well as for all the additional energy 'investments' that are required in order to carry out the same chain of processes. However, this general framework leaves the individual practitioner with a range of choices that can affect the results and thus, the conclusions of a NEA study. The current IEA PVPS guidelines were developed to provide guidance on assuring consistency, balance, and quality to enhance the credibility and reliability of the results from photovoltaic (PV) NEAs. The guidelines represent a consensus among the authors - PV NEA experts in North America and Europe - for assumptions made on PV performance, process inputs and outputs, methods of analysis, and reporting of the results. Guidance is given on photovoltaic-specific parameters used as inputs in NEA and on choices and assumptions in inventory data analysis and on implementation of modelling approaches. A consistent approach towards system modelling, the functional unit, the system boundaries and allocation aspects enhance the credibility of PV electricity NEA studies and enables balanced NEA-based comparisons. Specifically, "apples-to-oranges" comparisons of different energy carriers (e.g., fuels vs. electricity) are not methodologically sound and are to be avoided in all cases; also, any comparison across renewable and non-renewable electricity generation technologies must clearly point out the intrinsically short-term nature of the NEA viewpoint, which does not capture the long-term sustainability implications of renewable vs. non-renewable primary energy harvesting and use: non-renewable primary energy resources are depleted and finally exhausted (irrespective of the size of the EROI), while renewable primary energy resources are not. This document provides an in-depth discussion of a common metric of NEA, namely the energy return on investment (EROI), and how this is to be interpreted vis-a-vis the deceptively similar-sounding metrics in the field of Life Cycle Assessment (LCA): cumulative energy demand (CED) and non-renewable cumulative energy demand (nr-CED) per unit output. Specifically, a number of key differences are highlighted between these metrics as applied to electricity production systems, which are listed in Table S-1.

14 SOLAR ENERGY↗

Determining elastic anisotropy of textured polycrystals using resonant ultrasound spectroscopy

Abstract Polycrystalline materials can have complex anisotropic properties depending on their crystallographic texture and crystal structure. In this study, we use resonant ultrasound spectroscopy (RUS) to nondestructively quantify the elastic anisotropy in extruded aluminum alloy 1100-O, an inherently low-anisotropy material. Further, we show that RUS can be used to indirectly provide a description of the material’s texture, which in the present case is found to be transversely isotropic. By determining the entire elastic tensor, we can identify the level and orientation of the anisotropy originated during extrusion. The relative anisotropy of the compressive (c 11 /c 33 ) and shear (c 44 /c 66 ) elastic constants is 1.5% ± 0.5% and 5.7% ± 0.5%, respectively, where the elastic constants (five independent elastic constants for transversely isotropic) are those associated with the extrusion axis that defines the symmetry of the texture. These results indicate that the texture is expected to have transversely isotropic symmetry. This finding is confirmed by two additional approaches. First, we confirm elastic constants and the degree of elastic anisotropy by direct sound velocity measurements using ultrasonic pulse echo. Second, neutron diffraction (ND) data confirm the symmetry of the bulk texture consistent with extrusion-induced anisotropy, and polycrystal elasticity simulations using the elastic self-consistent model with input from ND textures and aluminum single-crystal elastic constants render similar levels of polycrystal elastic anisotropy to those measured by RUS. We demonstrate the ability of RUS to detect texture-induced anisotropy in inherently low-anisotropy materials. Therefore, as many other common materials have intrinsically higher elastic anisotropy, this technique should be applicable for similar levels of texture, providing an efficient general diagnostic and characterization tool.

36 MATERIALS SCIENCE↗

Shock compression of additively manufactured high solids loaded polymer composites with aligned porosity

The effects of aligned porosity on the shock-compression response of additively manufactured (AM) composite structures with collinear and log-cabin geometries are investigated. The composites contain two inorganic and two organic particle populations and a UV-curable polymer binder. X-ray phase contrast imaging (X-PCI) is used as an in-material diagnostic in plate-impact experiments performed at the Dynamic Compression Sector of the Advanced Photon Source at the Argonne National Laboratory. Macroscale shock and particle velocities and microscale pore collapse velocities are measured from X-PCI images obtained from samples impacted in various orientations relative to the AM build directions. The linear shock and particle velocity relation for the structures with collinear build geometry shows directional differences, with the build direction exhibiting the highest slope and the filament print direction having the shallowest slope. Composites with log-cabin geometry, due to their slightly lower porosity and smaller sized pores, show higher shock velocities than the collinear structures at the same particle velocity. Microscale directionality effects are also observed, with the pore collapse velocity dependent on the pore configuration. Specifically, the pore collapse velocity is highest for pores elongated along the impact direction which is the case for the colinear structures impacted in the filament print direction, which is consistent with the directionality trend observed in the data for the shock and particle velocity equation of state. The pore collapse velocity approaches ∼80 % of the shock velocity and is several times the average bulk particle velocity, suggesting a highly hydrodynamic mechanism of pore collapse. Overall, both the macroscale response as measured by the shock and particle velocity relationship, and the microscale response as measured by the pore collapse velocity, are found to be anisotropic and dependent on the AM composite structure.

Wagner, K. B. [Georgia Institute of Technology, At↗

Inclusive studies of two- and three-nucleon short-range correlations in 3 H and 3 He

Inclusive electron scattering at carefully chosen kinematics can isolate scattering from the high-momentum nucleons in short-range correlations (SRCs). SRCs are produced by the hard, short-distance interactions of nucleons in the nucleus, and because the two-nucleon (2N) SRCs arise from the same N-N interaction in all nuclei, the cross section in the SRC-dominated regime is identical up to an overall scaling factor. This scaling behavior has been used to identify SRC dominance and to measure the contribution of SRCs in a wide range of nuclei. We examine this scaling behavior over a range of momentum transfers using new data on 2 H, 3 H, and 3 He, and find an expanded scaling region compared to heavy nuclei. Motivated by this improved scaling, we examine the 3 H and 3 He data in kinematics where three-nucleon SRCs may play an important role. The data for the largest struck nucleon momenta are consistent with isolation of scattering from three-nucleon SRCs, and suggest that the very highest momentum nucleons in 3 He have a nearly isospin-independent momentum configuration.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Structural properties of aqueous grown polydopamine thin films determined by neutron reflectometry

Here, in this work, neutron reflectometry (NR) studies of the bio-mimetic polymer, polydopamine (PDA), deposited from differing initial concentrations of precursor material dopamine hydrochloride for a range of polymerization times, is reported. PDA can form a complex and highly versatile polymer film, with many structure studies having been performed previously, but a comprehensive structural determination of PDA by NR is lacking in the literature. It was found that simple box models were incapable of fully explaining the observed data, necessitating the use of a composite model consisting of the weighted average of both the 1 and 2 box models to fully capture the heterogeneous nature of the PDA film structure. Confocal laser scanning microscopy (CLSM) and atomic force microscopy (AFM) were performed to capture the surface structure and relative mechanical difference between the separate domains of the PDA. The CLSM results provide evidence that the PDA domains are larger than the coherent scattering length of a neutron used in these measurements, 10μm, supporting the need for a composite model. The AFM measurements show complex structure below the coherence length provide physical justification for the two box model. It was determined that film structure and quality are both heavily impacted by the initial concentration of dopamine hydrochloride and the polymerization time, giving confidence to the highly customizable nature of PDA as an adhesion promoting interface treatment in composite systems, such as plastic bonded explosives (PBX).

36 MATERIALS SCIENCE↗

The 1 H T 1 dispersion curve of fentanyl citrate to identify NQR parameters

We report the 1 H T 1 dispersion curve between 0 and 5 MHz for the synthetic opioid fentanyl citrate (C 28 H 36 N 2 O 8 ). The structures in the curve can be used to estimate the 14 N nuclear quadrupole resonance (NQR) frequencies of the material. Density functional theory predictions of the NQR parameters of several fentanyl citrate compounds are also reported. The predictions for the aniline nitrogen are consistent with structures in the observed T 1 data. To help interpret the fentanyl citrate results the T 1 dispersion curve for the explosive ammonium nitrate is also presented.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Dichotomous Temperature Response in the Electronic Structure of Epitaxially Grown Altermagnet MnTe

The altermagnet candidate MnTe has recently gained significant interest due to its unconventional magnetic ordering. One of the key features of altermagnetism is the momentum-dependent spin-split band and its temperaturedependent evolution. Yet a fully momentum-resolved experimental investigation, including out-of-plane direction, is still lacking. Here, we systematically investigate the electronic structure of epitaxially grown MnTe by using angle-resolved photoemission spectroscopy (ARPES). Our photon-energy-dependent ARPES data reveal significant out-of-plane dispersions consistent with previous theoretical calculations. More interestingly, we identify two distinct temperature-dependent electronic band structure evolutions at different out-of-plane momentum positions: momentum-dependent energy shifts at the nodal plane and substantial spectral weight suppression at the off-nodal plane. These findings may suggest the importance of considering both the itinerant and localized nature of the magnetic ordering and momentum-dependent interactions. Our work provides crucial insights into the complex correlation between momentum, temperature, and electronic structure in MnTe, contributing to a deeper understanding of altermagnetism.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Neutralization Short-Circuiting with Weak Electrolytes Erodes the Efficiency of Bipolar Membranes

Bipolar membranes (BPMs) are critical components of a variety of electrochemical energy technologies. Many electrochemical applications require the use of buffers to maintain stable, nonextreme pH environments, yet the impact of buffers or weak acids/bases on the electrochemical behavior of BPMs remains poorly understood. Here, our data for a cell containing weak electrolytes is consistent with internal pH gradients within the anion exchange membrane (AEM) or cation exchange membrane (CEM) component of the BPM that form via ionic short-circuiting processes at open-circuit. Short-circuiting results from the coupling of co-ion crossover and parasitic neutralization and leads to buffering of the bipolar interface. This phenomenon, which we term neutralization short-circuiting, serves to erode BPM efficiency by attenuating the open-circuit membrane voltage and introducing parasitic reverse bias currents associated with weak acid/base dissociation at the interface. These findings establish a mechanistic basis for the operation of BPM cells in the presence of weak acid/base electrolytes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Hydrology in the Age of Artificial Intelligence: From Fragmentation to Coherent Terrestrial Hydrosphere Science

The rapid rise of machine learning (ML) in hydrology has prompted debate about the discipline's scientific relevance. While ML often outperforms traditional models in streamflow prediction, we argue that this reflects a deeper limitation: persistent fragmentation of hydrological science itself. Narrow focus on isolated components has hindered the development of coherent, scale‐relevant understanding of the integrated terrestrial hydrosphere. This is illustrated, for example, by widely divergent estimates of groundwater–streamflow interactions and of water balance‐implied ongoing storage changes. We argue that hydrology's future lies not in choosing between ML and physics, but in integrating data‐driven and process‐based approaches to advance consistent, realistic, and societally relevant understanding of the terrestrial hydrosphere and its multifaceted roles in the Earth System.

Painter, Scott L. [Oak Ridge National Laboratory (↗

Chemical structure and genetic organization of the E. coli O6:K15 capsular polysaccharide

Capsular polysaccharides are important virulence factors in pathogenic bacteria. Characterizing the structural components and biosynthetic pathways for these polysaccharides is key to our ability to design vaccines and other preventative therapies that target encapsulated pathogens. Many gramnegative pathogens such as Neisseria meningitidis and Escherichia coli express acidic capsules. The E. coli K15 serotype has been identifed as both an enterotoxigenic and uropathogenic pathogen. Despite its relevance as a disease-causing serotype, the associated capsular polysaccharide remains poorly characterized. We describe in this report the chemical structure of the K15 polysaccharide, based on chemical analysis and nuclear magnetic resonance (NMR) data. The repeating structure of the K15 polysaccharide consists of 4)-α-GlcpNAc-(1→5)-α-KDOp-(2→partially O-acetylated at 3-hydroxyl of GlcNAc. We also report, the organization of the gene cluster responsible for capsule biosynthesis. We identify genes in this cluster that potentially encode an O-acetyltransferase, an N-acetylglucosamine transferase, and a KDO transferase consistent with the structure we report.

59 BASIC BIOLOGICAL SCIENCES↗

Steady global surface warming from 1973 to 2022 but increased warming rate after 1990

The change in global mean surface temperature is a crucial and broadly used indicator of the evolution of climate change. Any decadal scale changes in warming rate are however obfuscated by internal variability. Here we show that the surface temperature increase through the recent La Nina influenced years (2022) is consistent with the 50-year trend of 0.18 °C/decade. We use an Earth System Model based tool to filter out modulations to the warming rate by sea-surface temperature patterns and find consistent warming rates in four major global temperature data series. However, we also find clear indications, in all observational series, of a step-up in warming rate since around 1990. CMIP6 models generally do not capture this observed combination of long-term warming rate and recent increase.

58 GEOSCIENCES↗

Capacitance–voltage modeling of mid-wavelength infrared nBn detectors

Capacitance–voltage measurements are a powerful technique to determine doping profiles of semiconductor pn junctions and Schottky barrier diodes. The measurements were recently extended to III-V-based mid-wavelength nBn infrared detectors, and absorber doping densities have been extracted using the widely accepted Schottky approximation, where the potential drop across the device is assumed to be across the depleting absorber layer. However, this approach is limited to when the absorber region of the nBn is under high reverse bias and thus is only able to extract the absorber region doping profile. Here, we introduce a semi-analytical model that is capable of extracting barrier dopant polarity, doping concentration, and thickness, as well as contact and absorber layer doping concentrations, all from a capacitance–voltage measurement. Rather than solely considering the potential drop across the depleting layers, it considers the potential drop across the accumulating layer as well. This negative charge accumulation occurs for the contact and absorber layers in the case of reverse and forward biases, respectively. This allows for a single model to be applied to a capacitance–voltage curve at forward and reverse biases and it can provide regions of bias where the absorber transitions from depletion to accumulation. We compare the agreement of the semianalytical model with modeling results from commercially available finite element method software and experimental capacitance–voltage data. Finally, we show that the method is consistent with the Schottky approximation of extracting absorber doping densities at high reverse bias and discuss the model's limitations.

Physics↗